Classification of Emerging Neural Activity from Planning to Grasp Execution using a Novel EEG-Based BCI Platform
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909094413074432 |
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| author | Cetera, Anna Rabiee, Ali Ghafoori, Sima Abiri, Reza |
| author_facet | Cetera, Anna Rabiee, Ali Ghafoori, Sima Abiri, Reza |
| contents | There have been different reports of developing Brain-Computer Interface (BCI) platforms to investigate the noninvasive electroencephalography (EEG) signals associated with plan-to-grasp tasks in humans. However, these reports were unable to clearly show evidence of emerging neural activity from the planning (observation) phase - dominated by the vision cortices - to grasp execution - dominated by the motor cortices. In this study, we developed a novel vision-based grasping BCI platform that distinguishes different grip types (power and precision) through the phases of plan-to-grasp tasks using EEG signals. Using our platform and extracting features from Filter Bank Common Spatial Patterns (FBCSP), we show that frequency-band specific EEG contains discriminative spatial patterns present in both the observation and movement phases. Support Vector Machine (SVM) classification (power vs precision) yielded high accuracy percentages of 74% and 68% for the observation and movement phases in the alpha band, respectively. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_03493 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Classification of Emerging Neural Activity from Planning to Grasp Execution using a Novel EEG-Based BCI Platform Cetera, Anna Rabiee, Ali Ghafoori, Sima Abiri, Reza Signal Processing Neurons and Cognition There have been different reports of developing Brain-Computer Interface (BCI) platforms to investigate the noninvasive electroencephalography (EEG) signals associated with plan-to-grasp tasks in humans. However, these reports were unable to clearly show evidence of emerging neural activity from the planning (observation) phase - dominated by the vision cortices - to grasp execution - dominated by the motor cortices. In this study, we developed a novel vision-based grasping BCI platform that distinguishes different grip types (power and precision) through the phases of plan-to-grasp tasks using EEG signals. Using our platform and extracting features from Filter Bank Common Spatial Patterns (FBCSP), we show that frequency-band specific EEG contains discriminative spatial patterns present in both the observation and movement phases. Support Vector Machine (SVM) classification (power vs precision) yielded high accuracy percentages of 74% and 68% for the observation and movement phases in the alpha band, respectively. |
| title | Classification of Emerging Neural Activity from Planning to Grasp Execution using a Novel EEG-Based BCI Platform |
| topic | Signal Processing Neurons and Cognition |
| url | https://arxiv.org/abs/2402.03493 |